#StackBounty: #confidence-interval #estimation #penalized #constrained-regression Confidence limits for constrained penalized log likel…

Bounty: 50

I am estimating parameter $beta$ as:

hat beta &= mathop{mathrm{arg,max}}_beta ;; l(beta;X,y) – frac{lambda}{2}left(tilde y-g(beta,tilde X)right)^prime C^prime Cleft(tilde y-g(beta,tilde X)right)\
& ;;;;; Abetaleq 0\
& tilde y = (y^prime,y^{ast,prime})^prime\
&tilde X = (X^prime,X^{ast,prime})^prime\
& g(p,Q) = exp(Qp)

How should I go about estimating the confidence limits on $hat beta$ theoretically?

Get this bounty!!!

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